Journal cover Journal topic
Archives Animal Breeding Archiv Tierzucht
Journal topic

Journal metrics

IF value: 0.991
IF0.991
IF 5-year value: 1.217
IF 5-year
1.217
CiteScore value: 2.0
CiteScore
2.0
SNIP value: 1.055
SNIP1.055
IPP value: 1.27
IPP1.27
SJR value: 0.425
SJR0.425
Scimago H <br class='widget-line-break'>index value: 28
Scimago H
index
28
h5-index value: 13
h5-index13
Supported by
Logo Leibniz Institute for Farm Animal Biology Logo Leibniz Association
Volume 51, issue 2
Arch. Anim. Breed., 51, 120–128, 2008
https://doi.org/10.5194/aab-51-120-2008
© Author(s) 2008. This work is distributed under
the Creative Commons Attribution 3.0 License.
Arch. Anim. Breed., 51, 120–128, 2008
https://doi.org/10.5194/aab-51-120-2008
© Author(s) 2008. This work is distributed under
the Creative Commons Attribution 3.0 License.

  10 Oct 2008

10 Oct 2008

The relationship of parameters of body measures and body weight by using digital image analysis in pre-slaughter cattle

S. Ozkaya and Y. Bozkurt S. Ozkaya and Y. Bozkurt
  • Department of Animal Science, Faculty of Agriculture, Suleyman Demirel University, Isparta, Turkey

Abstract. The objective of this study was to predict body weight (BW) of pre-slaughtering beef cattle using digital image analysis. Data used in this study were collected from slaughterhouses in Isparta and nearby provinces from 140 animals. Selected body measurements such as body weight (BW), wither height (WH), body length (BL), chest depth (CD), hip width (HW), hip height (HH) and body area (BA) of different breeds of beef cattle were combined and compared by digital image analysis. The body area was included as a different parameter for prediction of BW instead of chest girth. However, regression equation that included only body area gave the lowest R2 value for Holstein (18.0%), but the R2 value was 43.2 and 51.7% for Brown Swiss and crossbred animals, respectively. The regression equation which included all body traits resulted in R2 values 35.3, 85.1, and 79.6% for Holstein, Brown Swiss and crossbred, respectively. The regression equation which included body area and body length showed that prediction ability of digital image analysis was high for prediction of BW in Brown Swiss and crossbred animals compared to Holsteins (R2 82.6, 76.5, and 29.5%, respectively). Results indicated that the prediction ability of digital image analysis was low for prediction of BW. Although possibility of using body area as a parameter in predicting BW is low it can be developed by further and better designed experiments.

Download
Citation